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Entry Level Civil Engineering Data Science Jobs in Bellingham, WA

Tidal Vision

Research Scientist

Bellingham, WA · On-site

$34 - $36/hr

... data, and presenting to research managers and project stakeholders. As a member of Cesco ... Help engineer scalable and commercially viable water treatment solutions for Cesco's sales team.

Tidal Vision

Research Scientist

Bellingham, WA · On-site

... a focus on engineered water treatment solutions forchitosan products to determine their ... Bachelorsof Science in a laboratory, physical or natural science field. * Working knowledge of ...

Tidal Vision

Research Scientist

Bellingham, WA

$34 - $36/hr

... a focus on engineered water treatment solutions forchitosan products to determine their ... Bachelorsof Science in a laboratory, physical or natural science field. * Working knowledge of ...

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All JobsCivil Engineering Data Science JobsEntry Level Civil Engineering Data Science JobsEntry Level Civil Engineering Data Science Jobs in Bellingham, WA

Entry Level Civil Engineering Data Science information

See Bellingham, WA salary details

$42.1K

$76.4K

$125.8K

How much do entry level civil engineering data science jobs pay per year?

As of Jul 26, 2026, the average yearly pay for entry level civil engineering data science in Bellingham, WA is $76,425.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,000.00 and $92,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Entry Level Civil Engineering Data Scientist, and why are they important?

To thrive as an Entry Level Civil Engineering Data Scientist, you need a solid grasp of civil engineering fundamentals, statistics, and data analysis, typically supported by a relevant engineering or data science degree. Familiarity with technical tools such as Python, MATLAB, AutoCAD, and data visualization platforms, as well as experience with databases and possibly certifications in data analytics, are highly beneficial. Strong problem-solving abilities, attention to detail, and communication skills make candidates stand out in this multidisciplinary role. These skills are crucial for accurately interpreting engineering data, supporting infrastructure decision-making, and effectively conveying insights to technical and non-technical stakeholders.

How do entry-level civil engineering data scientists typically collaborate with engineering teams on infrastructure projects?

Entry-level civil engineering data scientists often work closely with multidisciplinary engineering teams to collect, analyze, and interpret large datasets related to infrastructure projects. They support decision-making by creating predictive models, visualizations, and reports that inform project design, construction, and maintenance. Collaboration usually involves regular meetings, sharing insights with engineers and project managers, and ensuring that data-driven recommendations align with technical and regulatory requirements. This partnership helps bridge the gap between data science and practical engineering solutions.

What is the difference between Entry Level Civil Engineering Data Science vs Entry Level Civil Engineering?

AspectEntry Level Civil Engineering Data ScienceEntry Level Civil Engineering
Required CredentialsBachelor's in Civil Engineering, Data Science, or related field; knowledge of programming and data analysisBachelor's in Civil Engineering or related field; engineering fundamentals
Work EnvironmentDesign firms, consulting agencies, government agencies with data analysis focusConstruction sites, design offices, infrastructure projects
Employer & Industry UsageUtilized in infrastructure planning, data-driven decision making, modelingDesign, construction, and maintenance of civil infrastructure

Entry Level Civil Engineering Data Science combines civil engineering fundamentals with data analysis skills, focusing on data-driven project optimization. In contrast, Entry Level Civil Engineering emphasizes traditional engineering design and construction. Both roles require a bachelor's degree, but the data science role demands additional programming and analytical skills, often working in environments that leverage data for infrastructure planning and management.

Is 30 too late for data science?

Entry level civil engineering data science roles typically value skills and relevant experience over age. Many professionals transition into data science later in their careers by acquiring programming, statistical, and data analysis skills through courses or certifications, making 30 not too late to start in this field.

Can you make $500,000 as a civil engineer?

Entry level civil engineering data science roles typically do not pay $500,000 annually; such high salaries are usually associated with senior positions, specialized consulting, or executive roles. Most civil engineers earn between $60,000 and $120,000 per year, with higher earnings possible through experience, advanced skills, or management responsibilities.

Can I get a data scientist job with no experience?

Entry level civil engineering data science roles typically require some foundational knowledge in data analysis, programming (such as Python or R), and understanding of civil engineering concepts. While prior experience is not always mandatory, demonstrating relevant skills through projects, certifications, or coursework can improve chances of securing such positions.

What is an entry level civil engineering data science job?

An entry level civil engineering data science job involves using data analysis and computational tools to solve problems related to civil engineering, such as infrastructure design, construction, and maintenance. Professionals in this role work with large datasets from sensors, surveys, and simulations to help inform decisions about projects like roads, bridges, and buildings. They often use programming languages like Python or R and work with statistical methods, machine learning, and data visualization. This role is ideal for recent graduates with skills in both civil engineering fundamentals and data science techniques.

Can a civil engineer become a data scientist?

A civil engineer can become a data scientist by acquiring skills in programming, statistics, and data analysis tools such as Python, R, and SQL. Transitioning often involves additional training or education in data science concepts and gaining experience with machine learning and data visualization. Many professionals successfully make this shift by leveraging their analytical background and pursuing relevant certifications or courses.
What are popular job titles related to Entry Level Civil Engineering Data Science jobs in Bellingham, WA? For Entry Level Civil Engineering Data Science jobs in Bellingham, WA, the most frequently searched job titles are:
What job categories do people searching Entry Level Civil Engineering Data Science jobs in Bellingham, WA look for? The top searched job categories for Entry Level Civil Engineering Data Science jobs in Bellingham, WA are:
What cities near Bellingham, WA are hiring for Entry Level Civil Engineering Data Science jobs? Cities near Bellingham, WA with the most Entry Level Civil Engineering Data Science job openings:
Entry Level Civil Engineering Data Science jobs near you
Infographic showing various Entry Level Civil Engineering Data Science job openings in Bellingham, WA as of July 2026, with employment types broken down into 81% Full Time, 16% Part Time, 1% Temporary, and 2% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $76,425 per year, or $36.7 per hour.
Data Scientist-Direct Hire

Data Scientist-Direct Hire

US Department of the Treasury

Bellingham, WA • On-site

$74K/yr

Other

Posted 20 days ago

U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

302nd of 832 rated public administrative organizations

Job description

WHAT IS DATA AND ANALYTICS (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position(s) are to be filled in the following area(s):
    • DAO - DATA AND ANALYTICS
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
BASIC REQUIREMENTS All GRADES: EDUCATION:
You must have a bachelor's or higher degree in mathematics, statistics, computer science, data science or other field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: You may qualify with an equivalent combination of qualifying experience and education with at least 30 semester hours related to Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
EDUCATION/SPECIALIZED EXPERIENCE FOR GS-11: In addition to meeting basic requirements, to be eligible for this position, you must have at least one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal Service. Specialized experience for this position includes: Applying descriptive or inferential statistical methods to analyze data, identify trends or patterns, evaluate results, and develop findings, reports, or recommendations; Using programming, query, or scripting languages, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to extract, transform, analyze, or prepare data for analysis; Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform); Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings; and Creating reports, dashboards, visualizations, written summaries, or presentations to communicate statistical or technical findings to technical or non-technical audiences.
OR
EDUCATION: You may substitute education for specialized experience as follows: A Ph.D. or equivalent doctoral degree as described in the basic requirements in mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
Three (3) full academic years of progressively higher-level graduate education leading to a PH.D or equivalent doctoral degree in mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: You may qualify with an equivalent combination of qualifying experience and education.
SPECIALIZED EXPERIENCE GRADE 12: In addition to the basic requirements above, to be eligible for this position at the GS-12 level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
  • Planning and carrying out data analysis assignments by applying descriptive or inferential statistical methods to analyze data from multiple sources, validate results, identify trends or patterns, and develop findings, reports, or recommendations.
  • Using programming, query, or scripting languages, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to extract, transform, validate, analyze, visualize, or document structured or unstructured data for data science projects.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, prescriptive analysis, or exploratory data analysis, to evaluate data, models, programs, or operations and make projections or recommendations.
  • Creating and presenting reports, dashboards, visualizations, written summaries, or presentations that explain statistical or technical methods, findings, limitations, or recommendations to managers, stakeholders, customers, or project teams.

SPECIALIZED EXPERIENCE GRADE 13: In addition to the basic requirements above, to be eligible for this position at the GS-13 level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
  • Independently planning and carrying out data science or statistical analysis projects by defining analytic questions, selecting data sources or methods, analyzing structured or unstructured data, validating results, and developing findings or recommendations.
  • Developing or applying statistical, machine learning, operations research, or other data science methods to evaluate programs, operations, compliance, or organizational performance, for example forecasting, predictive or prescriptive modeling, optimization, natural language processing or text analytics, graph or link analysis, or exploratory data analysis.
  • Using programming, query, scripting, or analytic tools, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to prepare, transform, document, analyze, and visualize data for data science projects.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Documenting analytic approaches, assumptions, limitations, validation results, success measures, or key performance indicators, and presenting technical findings or recommendations to managers, stakeholders, customers, or cross-functional teams.

AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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